A tutorial overview of flowPloidy
is available on
the
Bioconductor website.
This vignette is provided with the package, so once you have flowPloidy
installed you can access it from with R (see below).
flowPloidy
is available in Bioconductor.
To install it, you need to install the bioconductor
R package (more
details on the Bioconductor site ):
## try http:// if https:// URLs are not supported
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install()
Once that's installed, you can install flowPloidy
using the Bioconductor
tools:
BiocManager::install("flowPloidy")
BiocManager::install("flowPloidyData") # (optional) data for the examples
This should pull in all the package dependencies for flowPloidy
, after
which you can load the package with the normal function
library("flowPloidy")
.
To install the development version, use the following code:
## Install Bioconductor tools first:
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install()
## Install flowCore from Bioconductor:
BiocManager::install("flowCore")
## Install devtools so you can directly access GitHub
install.packages(devtools)
library(devtools)
## Install flowPloidy:
install_github("plantarum/flowPloidy", dependencies = TRUE,
build_vignettes = TRUE)
If the last command fails, particularly with complaints about building a
vignette, or reference to Pandoc, try with build_vignettes = FALSE
instead.
Note that I haven't yet updated the documentation to describe the
endopolyploidy analysis. To use the endopolyploidy workflow, you need to
use g2 = FALSE
in your call to FlowHist
or batchFlowHist
. This
excludes the g2 peaks from peak fitting, treating each peak as an
independent group of cells. You may also want to increase the samples
argument to match the number of peaks; however, you can correct this in
browseFlowHist
, so that's not critical.
## loading files for endopolyploidy analysis:
batch1 <- batchFlowHist(endo_files, channel="FL3.INT.LIN", g2 = FALSE,
samples = 5)
batch1 <- browseFlowHist(batch1)
Expanding flowPloidy
to handle up to six peaks (and now potentially an
unlimited number if needed) required reworking a bunch of the existing
code, and as part of this the column headings in the tables produced by
tabulateFlowHist
are now different from the previous release.
library("flowPloidy")
The flowPloidy
workflow is documented in the vignette, which you can view
from R:
fpVig <- vignette("flowPloidy-overview")
fpVig ## open vignette in a browser
edit(name = fpVig) ## open vignette source code in a text editor
It is also available online.
For general help using the package, you can post questions on
the Bioconductor Support Site. Use the
tag flowploidy
to ensure your question is brought to my attention.
The development repository for flowPloidy
is
on Github, and you can file bugs
there using the issues tab. You are also welcome to contribute features
or bug-fixes via pull requests!